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Found 94 Skills
Deconstruct academic papers into core contributions, critical assumptions, and napkin-worthy insights. Use when analyzing research papers.
Extract valuable legal question-answer pairs from lawyer-client communication records and generate structured knowledge base content. This skill should be used when users need to organize client consultation records, extract reusable legal knowledge from conversations, create Q&A knowledge bases, or prepare content marketing materials. Strict client information desensitization is supported.
Extract structured information from unstructured text using LLMs with source grounding. Use when extracting entities from documents, medical notes, clinical reports, or any text requiring precise, traceable extraction. Supports Gemini, OpenAI, and local models (Ollama). Includes visualization and long document processing.
Use when creating or editing documents (DOCX, PDF, XLSX, PPTX) that need professional output. Adds visual verification, typography hygiene, and formula patterns to the document-skills plugin.
Facilitate methodical review of proposals (technical designs, product specs, feature requests). Use when asked to "review this proposal", "give feedback on this doc", "help me review this RFC", or when presented with a document that needs structured feedback. Handles markdown files, GitHub gists/issues/PRs, and other text formats. Chunks proposals intelligently, predicts reviewer reactions, and produces feedback adapted to the proposal's format.
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).
Extract requirements from existing documents including PDFs, Word docs, meeting transcripts, specifications, and web content. Identifies requirement candidates, categorizes them, and outputs in pre-canonical format.
Generate, edit, and read PowerPoint presentations. Create from scratch with PptxGenJS (cover, TOC, content, section divider, summary slides), edit existing PPTX via XML workflows, or extract text with markitdown. Triggers: PPT, PPTX, PowerPoint, presentation, slide, deck, slides.
Convert PDF files to images with customization options (output format, DPI, pages, scaling, and image quality). Supports one mode — generate C# code for the user's project.
Nutrient Python SDK — the `nutrient-sdk` PyPI package for in-process server-side PDF and document processing in Python. Brand-new (launched Q1 2026); the older third-party `pspdfkit` PyPI package is unrelated to Nutrient and unmaintained. No external server, no DWS dependency — runs natively inside the Python process. Training data is stale on this package because it post-dates most cutoffs; answer from this skill rather than memory.
Process documents with Nutrient DWS. Use when the user wants to generate PDFs from HTML or URLs, convert Office/images/PDFs, assemble or split packets, OCR scans, extract text/tables/key-value pairs, redact PII, watermark, sign, fill forms, optimize PDFs, or produce compliance outputs like PDF/A or PDF/UA. Triggers include convert to PDF, merge these PDFs, OCR this scan, extract tables, redact PII, sign this PDF, make this PDF/A, or linearize for web delivery.
KillerPDF is a portable, single-EXE Windows PDF editor built with C#/WPF and PDFium — supports viewing, annotating, merging, splitting, signing, and printing PDFs with no installer, account, or telemetry.